LDE融合光谱回归分类的光照变化人脸识别.pdfVIP

154 2014 ，50（11） Computer Engineering and Applications 计算机工程与应用 LDE 融合光谱回归分类的光照变化人脸识别 1 2 周柏清 ，任勇军 1 2 ZHOU Baiqing , REN Yongjun 1.湖州职业技术学院 信息工程分院，浙江 湖州 313000 2.南京信息工程大学 计算机与软件学院，南京 210044 1.Faculty of Information Technology, Huzhou Vocational Technical College, Huzhou, Zhejiang 313000, China 2.School of Computer Software, Nanjing University of Information Science Technology, Nanjing 210044, China ZHOU Baiqing, REN Yongjun. Fusion of spectral regression classification with LDE for face recognition with illu- mination variation. Computer Engineering and Applications, 2014, 50 （11）：154-158. Abstract ：The performance of face recognition with illumination variation is impacted seriously by using traditional spec- tral regression algorithms to extract features, so an algorithm of spectral regression classification optimized by local dis- criminative embedding is proposed. Feature vectors of training samples are calculated. Local discriminative embedding is used to construct embedding needed by classification and embeddings needed by sub-manifold of each classification is learned based on neighbor and classification relationship. Spectral regression classification algorithm is used to compute project metrics, nearest neighbor classifier is used to finish face recognition. The effectiveness and robustness of proposed algorithm has been verified by experiments on the two common face databases extended YaleB and CMU PIE. Experimental results show that proposed algorithm has higher recognition accuracy, better operating characteristic and simpler calculate complexity clearly than several other spectral regression algorithms. Key words ：illumination variation; face recognition; local discriminant embedding; spectral regression classification; nearest neighbor classifier 摘 要：针对光照变化人脸识别问题中传统的光谱回归算法不能很好地进行特征提取而严重影响识别性能的问题， 提出了局部判别嵌入优化光谱回归分类的人脸识别算法。计算出训练样本的特征向量；借助于数据